Methods for classification of the type described are known. In particular, in bio-medical applications, for example, objects are labeled with very special markers of different characteristics, namely with fluorescence markers. This allows individual object regions of biological objects to be selectively labeled and represented after detection by a confocal scanning microscope. Usually, an object is labeled with several markers of different characteristics which each emit fluorescent light of a different wavelength range.
The fluorescent light of different wavelength ranges is detected by several detectors of the confocal scanning microscope which have different detection characteristics. The detectors detect the intensity of the light coming from the markers, in each case generating a detection signal which is dependent on the detected light intensity. Depending on the scanning procedure of the confocal scanning microscope, the detected detection signal is assigned to individual image elements, so-called “pixels”, of a multidimensional image.
The evaluation of the detection signals or of the object images obtained therefrom is always problematic because often the wavelength ranges of the fluorescent light emitted by the markers overlap spectrally. Not least because of this, a detector detects, for example, fluorescent light that should actually be detected by another detector. This phenomenon is also referred to by the term “crosstalk”. First of all, the crosstalk of an object detection can be avoided or minimized in that the wavelength ranges within which the detectors of the confocal scanning microscope detect, or are sensitive, are separated from each other to the greatest extent possible using optical filters, such as low-pass, high-pass or bandpass filters. However, this is not completely possible in cases where the wavelength ranges of the fluorescent light emitted by the markers overlap. In these cases, complete separation of the detection signals of the different detectors is not so easily possible. Furthermore, it is possible to detect only one marker during each scanning operation, for example, by illuminating the object with light of only one wavelength that is suitable for fluorescence excitation of this marker. However, when using different markers that can be excited with the same wavelength, selective excitation of the markers is then no longer possible.
Another approach is described in the literature reference “Multi-Spectral Imaging and Linear Unmixing Add a Whole New Dimension to Laser Scanning Fluorescence Microscopy”, BioTechniques 2001, Vol. 31, No. 6, 1272–1278, which first gives a brief overview of the classification methods used in the prior art of which the “linear unmixing” method appears to be very particularly suitable for confocal laser scanning fluorescence microscopy. To carry out this classification method, the spectrum of the light emitted by the markers is detected for each image element or pixel by a suitable sensor. Then, the detected spectrum can be represented by a linear combination of the emission spectra of the markers. In most cases, the emission spectrum of a marker that has been used is known or can be measured so that, after the detection, the coefficients of the linear combination need to be determined, thus allowing the object regions to be classified. This can be done, for example, using methods of linear algebra. However, for this purpose, it is necessary to detect the entire emission spectrum of each object image region emitted by the marker. This is possible using the LSM 510 META confocal scanning microscope described in the literature reference, with which spectrum detection is carried out using 32 individual channels, each having a wavelength range of about 10 nm. If such a detection is not possible, the classification method presented in this literature reference produces only inadequate results.
Especially when using a number of markers of different characteristics greater than the number of available detectors of the confocal scanning microscope, detection and subsequent classification of the light coming from the individual markers is problematic because a detector capable of detecting this light more or less selectively is not available for the light of each individual marker.